Eeg Decoding

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

24 shown of 24 papers with code (74 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Deep learning with convolutional neural networks for EEG decoding and visualization
  15 Mar 2017 5 repositories listed
  PLEASE READ AND CITE THE REVISED VERSION at Human Brain Mapping: http://onlinelibrary.
• Time-space-frequency feature Fusion for 3-channel motor imagery classification
  4 Apr 2023 3 repositories listed
  TSFF-Net comprises four main components: time-frequency representation, time-frequency feature extraction, time-space feature extraction, and feature fusion and classification.
• Transformer-based Spatial-Temporal Feature Learning for EEG Decoding
  11 Jun 2021 3 repositories listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  As far as we know, it is the first time that a detailed and complete method based on the transformer idea has been proposed in this field.
• Physics-inform attention temporal convolutional network for EEG-based motor imagery classification
  1 Aug 2022 2 repositories listed
  In this paper, we propose an attention-based temporal convolutional network (ATCNet) for EEG-based motor imagery classification.
• DBConformer: Dual-Branch Convolutional Transformer for EEG Decoding
  26 Jun 2025 1 repository listed
  It integrates a temporal Conformer to model long-range temporal dependencies and a spatial Conformer to extract inter-channel interactions, capturing both temporal dynamics and spatial patterns in EEG signals.
• TCANet: A Temporal Convolutional Attention Network for Motor Imagery EEG Decoding
  15 Jun 2025 1 repository listed
  This study proposes the Temporal Convolutional Attention Network (TCANet), a novel end-to-end model that hierarchically captures spatiotemporal dependencies by progressively integrating local, fused, and global features.
• EEG-CLIP : Learning EEG representations from natural language descriptions
  18 Mar 2025 1 repository listed
  Deep networks for electroencephalogram (EEG) decoding are currently often trained to only solve a specific task like pathology or gender decoding.
• MVCNet: Multi-View Contrastive Network for Motor Imagery Classification
  18 Feb 2025 1 repository listed
  Two contrastive modules are further introduced: a cross-view contrastive module that enforces consistency of original and augmented views, and a cross-model contrastive module that aligns features extracted from both…
• CBraMod: A Criss-Cross Brain Foundation Model for EEG Decoding
  10 Dec 2024 1 repository listed Syntology ran 2 of 5 samples · 3 unverified
  Secondly, existing EEG foundation models have limited generalizability on a wide range of downstream BCI tasks due to varying formats of EEG data, making it challenging to adapt to.
• CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification
  30 Aug 2024 1 repository listed
  In subject-specific evaluations, CTNet achieved remarkable decoding accuracies of 82.
• Geometric Neural Network based on Phase Space for BCI-EEG decoding
  8 Mar 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Taking advantage of the Augmented Covariance Method and the framework of SPDNet, we propose the Phase-SPDNet architecture and analyze its performance and the interpretability of the results.
• Spatial Variation Generation Algorithm for Motor Imagery Data Augmentation: Increasing the Density of Sample Vicinity
  12 Sep 2023 1 repository listed
  Moreover, SVG generates a uniform distribution and stabilizes the training process of models.
• Aggregating Intrinsic Information to Enhance BCI Performance through Federated Learning
  14 Aug 2023 1 repository listed
  Though numerous research groups and institutes collect a multitude of EEG datasets for the same BCI task, sharing EEG data from multiple sites is still challenging due to the heterogeneity of devices.
• Weight Freezing: A Regularization Approach for Fully Connected Layers with an Application in EEG Classification
  9 Jun 2023 1 repository listed
  The concept of weight freezing revolves around the idea of reducing certain neurons' influence on the decision-making process for a specific EEG task by freezing specific weights in the fully connected layer during the…
• Deep Riemannian Networks for End-to-End EEG Decoding
  20 Dec 2022 1 repository listed
  Our study aims to lay the groundwork in the area of these topics through the analysis of DRNs for EEG with a wide range of hyperparameters.
• Enhancing Low-Density EEG-Based Brain-Computer Interfaces with Similarity-Keeping Knowledge Distillation
  6 Dec 2022 1 repository listed
  Our framework includes a newly proposed similarity-keeping (SK) teacher-student KD scheme that encourages a low-density EEG student model to acquire the inter-sample similarity as in a pre-trained teacher model trained…
• Embedding neurophysiological signals
  25 Oct 2022 1 repository listed
  Neurophysiological time-series recordings of brain activity like the electroencephalogram (EEG) or local field potentials can be decoded by machine learning models in order to either control an application, e.
• fMRI from EEG is only Deep Learning away: the use of interpretable DL to unravel EEG-fMRI relationships
  23 Oct 2022 1 repository listed
  The access to activity of subcortical structures offers unique opportunity for building intention dependent brain-computer interfaces, renders abundant options for exploring a broad range of cognitive phenomena in the…
• MAtt: A Manifold Attention Network for EEG Decoding
  5 Oct 2022 1 repository listed Syntology ran 0 of 9 samples · 9 unverified
  Recognition of electroencephalographic (EEG) signals highly affect the efficiency of non-invasive brain-computer interfaces (BCIs).
• ExBrainable: An Open-Source GUI for CNN-based EEG Decoding and Model Interpretation
  10 Jan 2022 1 repository listed
  We have developed a graphic user interface (GUI), ExBrainable, dedicated to convolutional neural networks (CNN) model training and visualization in electroencephalography (EEG) decoding.
• Uncertainty Detection and Reduction in Neural Decoding of EEG Signals
  28 Dec 2021 1 repository listed
  In this work, we proposed an uncertainty estimation and reduction model (UNCER) to quantify and mitigate the uncertainty during the EEG decoding process.
• Decoding kinetic features of hand motor preparation from single‐trial EEG using convolutional neural networks
  11 Aug 2020 1 repository listed
  These results show that movement speed and force can be accurately predicted from single‐trial EEG, and that the prediction strategies may provide useful neurophysiological information about motor preparation.
• Subject-Aware Contrastive Learning for Biosignals
  30 Jun 2020 1 repository listed
  Datasets for biosignals, such as electroencephalogram (EEG) and electrocardiogram (ECG), often have noisy labels and have limited number of subjects (<100).
• Decoding P300 Variability using Convolutional Neural Networks
  14 Jun 2019 1 repository listed
  Deep convolutional neural networks (CNN) have previously been shown to be useful tools for signal decoding and analysis in a variety of complex domains, such as image processing and speech recognition.

Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.